Using fuzzy logic models to reveal farmers' motives to integrate livestock, fish, and crops

Research output: Thesisinternal PhD, WU

Abstract

Rural extension services have changed paradigm and shifted to more participatory approaches, whereas in common mathematical models of farming systems, farmers’ motivation is solely represented by ‘utility maximisation’. While globally, farmers specialise, in Vietnam the rice-based systems have diversified into more sustainable integrated agriculture–aquaculture. We gathered data from 144 farms in six villages in two ecological zones of the Mekong Delta, Vietnam. Using the livelihood framework we conceptualised farmers’ decision-making in a fuzzy logic model that can deal with subjective linguistic statements through ‘if–then’ rules. The desire to improve livelihoods and diet, mainly for their children’ well-being was the farmers’ main motive for diversification. Livestock, including fish, was essential in the expansion and accumulation stages of the nuclear families’ life-course having five stages. In 10 recursive steps we developed a model of farmers’ decision-making in a transparent hierarchical tree composed of several Mamdani-based inference systems, each with its rule base. Model conceptualisation, variables selection, model structuring, and definition of linguistic values, membership functions and rule base were based on a first set of data that was completed before calibration. In a pilot, the simulation of the frequency distribution of four fish-production systems was good, but classification of individual farmers was poor. Using composed variables for land, water, labour and capital decreased the fuzziness of the inference in this pilot model. In a more elaborated three-layer model, the whole farm composition was simulated using variables for the production factors, farmers’ appreciation of prices, farmer’s know-how of 10 activities, operational variables of social motives for integration and diversification as well as for risk-taking behaviour and for rice food security. Model’s classification of individual farmers in the delta was good for the land-based activities but poor for the livestock activities. A test on the hill farmers’ dataset showed that the model was context-specific. The model’s sensitivity to the social variables determining diversification and integration was of the same magnitude as its sensitivity to product’s prices and farmer’s know-how, but smaller than its sensitivity to labour, capital and land endowment. We conclude that farmers’ decision-making can be simulated using a fuzzy logic model. In the Mekong Delta farm diversification and integration are driven by labour, income, homestead area, number of young children, index of integration, household life-course, and level of education and age of the household head, in decreasing order. The choice of a component depends on the household’s assets and specific know-how, and on marketability. Farm models that do not include family-related motivations might be less reliable than generally suggested.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • Verreth, Johan, Promotor
  • Udo, Henk, Co-promotor
  • van den Berg, J., Co-promotor
  • Kaymak, U., Co-promotor, External person
Award date18 Dec 2007
Place of Publication[S.l.]
Publisher
Print ISBNs9789085047803
Publication statusPublished - 2007

Fingerprint

fuzzy logic
livestock
farmers
crops
fish
decision making
households
farms
labor
livelihood
Vietnam
nuclear family
taxonomy
rice
risk behavior
ecological zones
family relations
fish production
assets
educational status

Keywords

  • farmers
  • motivation
  • fuzzy logic
  • simulation models
  • decision making
  • livestock farming
  • fish culture
  • crop husbandry
  • vietnam
  • integrated farming systems

Cite this

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title = "Using fuzzy logic models to reveal farmers' motives to integrate livestock, fish, and crops",
abstract = "Rural extension services have changed paradigm and shifted to more participatory approaches, whereas in common mathematical models of farming systems, farmers’ motivation is solely represented by ‘utility maximisation’. While globally, farmers specialise, in Vietnam the rice-based systems have diversified into more sustainable integrated agriculture–aquaculture. We gathered data from 144 farms in six villages in two ecological zones of the Mekong Delta, Vietnam. Using the livelihood framework we conceptualised farmers’ decision-making in a fuzzy logic model that can deal with subjective linguistic statements through ‘if–then’ rules. The desire to improve livelihoods and diet, mainly for their children’ well-being was the farmers’ main motive for diversification. Livestock, including fish, was essential in the expansion and accumulation stages of the nuclear families’ life-course having five stages. In 10 recursive steps we developed a model of farmers’ decision-making in a transparent hierarchical tree composed of several Mamdani-based inference systems, each with its rule base. Model conceptualisation, variables selection, model structuring, and definition of linguistic values, membership functions and rule base were based on a first set of data that was completed before calibration. In a pilot, the simulation of the frequency distribution of four fish-production systems was good, but classification of individual farmers was poor. Using composed variables for land, water, labour and capital decreased the fuzziness of the inference in this pilot model. In a more elaborated three-layer model, the whole farm composition was simulated using variables for the production factors, farmers’ appreciation of prices, farmer’s know-how of 10 activities, operational variables of social motives for integration and diversification as well as for risk-taking behaviour and for rice food security. Model’s classification of individual farmers in the delta was good for the land-based activities but poor for the livestock activities. A test on the hill farmers’ dataset showed that the model was context-specific. The model’s sensitivity to the social variables determining diversification and integration was of the same magnitude as its sensitivity to product’s prices and farmer’s know-how, but smaller than its sensitivity to labour, capital and land endowment. We conclude that farmers’ decision-making can be simulated using a fuzzy logic model. In the Mekong Delta farm diversification and integration are driven by labour, income, homestead area, number of young children, index of integration, household life-course, and level of education and age of the household head, in decreasing order. The choice of a component depends on the household’s assets and specific know-how, and on marketability. Farm models that do not include family-related motivations might be less reliable than generally suggested.",
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author = "R.H. Bosma",
note = "WU thesis, nr. 4348",
year = "2007",
language = "English",
isbn = "9789085047803",
publisher = "S.n.",
school = "Wageningen University",

}

Using fuzzy logic models to reveal farmers' motives to integrate livestock, fish, and crops. / Bosma, R.H.

[S.l.] : S.n., 2007. 144 p.

Research output: Thesisinternal PhD, WU

TY - THES

T1 - Using fuzzy logic models to reveal farmers' motives to integrate livestock, fish, and crops

AU - Bosma, R.H.

N1 - WU thesis, nr. 4348

PY - 2007

Y1 - 2007

N2 - Rural extension services have changed paradigm and shifted to more participatory approaches, whereas in common mathematical models of farming systems, farmers’ motivation is solely represented by ‘utility maximisation’. While globally, farmers specialise, in Vietnam the rice-based systems have diversified into more sustainable integrated agriculture–aquaculture. We gathered data from 144 farms in six villages in two ecological zones of the Mekong Delta, Vietnam. Using the livelihood framework we conceptualised farmers’ decision-making in a fuzzy logic model that can deal with subjective linguistic statements through ‘if–then’ rules. The desire to improve livelihoods and diet, mainly for their children’ well-being was the farmers’ main motive for diversification. Livestock, including fish, was essential in the expansion and accumulation stages of the nuclear families’ life-course having five stages. In 10 recursive steps we developed a model of farmers’ decision-making in a transparent hierarchical tree composed of several Mamdani-based inference systems, each with its rule base. Model conceptualisation, variables selection, model structuring, and definition of linguistic values, membership functions and rule base were based on a first set of data that was completed before calibration. In a pilot, the simulation of the frequency distribution of four fish-production systems was good, but classification of individual farmers was poor. Using composed variables for land, water, labour and capital decreased the fuzziness of the inference in this pilot model. In a more elaborated three-layer model, the whole farm composition was simulated using variables for the production factors, farmers’ appreciation of prices, farmer’s know-how of 10 activities, operational variables of social motives for integration and diversification as well as for risk-taking behaviour and for rice food security. Model’s classification of individual farmers in the delta was good for the land-based activities but poor for the livestock activities. A test on the hill farmers’ dataset showed that the model was context-specific. The model’s sensitivity to the social variables determining diversification and integration was of the same magnitude as its sensitivity to product’s prices and farmer’s know-how, but smaller than its sensitivity to labour, capital and land endowment. We conclude that farmers’ decision-making can be simulated using a fuzzy logic model. In the Mekong Delta farm diversification and integration are driven by labour, income, homestead area, number of young children, index of integration, household life-course, and level of education and age of the household head, in decreasing order. The choice of a component depends on the household’s assets and specific know-how, and on marketability. Farm models that do not include family-related motivations might be less reliable than generally suggested.

AB - Rural extension services have changed paradigm and shifted to more participatory approaches, whereas in common mathematical models of farming systems, farmers’ motivation is solely represented by ‘utility maximisation’. While globally, farmers specialise, in Vietnam the rice-based systems have diversified into more sustainable integrated agriculture–aquaculture. We gathered data from 144 farms in six villages in two ecological zones of the Mekong Delta, Vietnam. Using the livelihood framework we conceptualised farmers’ decision-making in a fuzzy logic model that can deal with subjective linguistic statements through ‘if–then’ rules. The desire to improve livelihoods and diet, mainly for their children’ well-being was the farmers’ main motive for diversification. Livestock, including fish, was essential in the expansion and accumulation stages of the nuclear families’ life-course having five stages. In 10 recursive steps we developed a model of farmers’ decision-making in a transparent hierarchical tree composed of several Mamdani-based inference systems, each with its rule base. Model conceptualisation, variables selection, model structuring, and definition of linguistic values, membership functions and rule base were based on a first set of data that was completed before calibration. In a pilot, the simulation of the frequency distribution of four fish-production systems was good, but classification of individual farmers was poor. Using composed variables for land, water, labour and capital decreased the fuzziness of the inference in this pilot model. In a more elaborated three-layer model, the whole farm composition was simulated using variables for the production factors, farmers’ appreciation of prices, farmer’s know-how of 10 activities, operational variables of social motives for integration and diversification as well as for risk-taking behaviour and for rice food security. Model’s classification of individual farmers in the delta was good for the land-based activities but poor for the livestock activities. A test on the hill farmers’ dataset showed that the model was context-specific. The model’s sensitivity to the social variables determining diversification and integration was of the same magnitude as its sensitivity to product’s prices and farmer’s know-how, but smaller than its sensitivity to labour, capital and land endowment. We conclude that farmers’ decision-making can be simulated using a fuzzy logic model. In the Mekong Delta farm diversification and integration are driven by labour, income, homestead area, number of young children, index of integration, household life-course, and level of education and age of the household head, in decreasing order. The choice of a component depends on the household’s assets and specific know-how, and on marketability. Farm models that do not include family-related motivations might be less reliable than generally suggested.

KW - boeren

KW - motivatie

KW - vage logica

KW - simulatiemodellen

KW - besluitvorming

KW - veehouderij

KW - visteelt

KW - landbouwplantenteelt

KW - vietnam

KW - geïntegreerde bedrijfssystemen

KW - farmers

KW - motivation

KW - fuzzy logic

KW - simulation models

KW - decision making

KW - livestock farming

KW - fish culture

KW - crop husbandry

KW - vietnam

KW - integrated farming systems

M3 - internal PhD, WU

SN - 9789085047803

PB - S.n.

CY - [S.l.]

ER -